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<div class="header">
  <div class="summary">
<a href="classEigen_1_1IncompleteCholesky-members.html">List of all members</a> &#124;
<a href="#pub-methods">Public Member Functions</a>  </div>
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<div class="title">Eigen::IncompleteCholesky&lt; Scalar, UpLo_, OrderingType_ &gt; Class Template Reference</div>  </div>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><h3>template&lt;typename Scalar, int UpLo_ = Lower, typename OrderingType_ = AMDOrdering&lt;int&gt;&gt;<br />
class Eigen::IncompleteCholesky&lt; Scalar, UpLo_, OrderingType_ &gt;</h3>

<p>Modified Incomplete Cholesky with dual threshold. </p>
<p>References : C-J. Lin and J. J. Moré, Incomplete Cholesky Factorizations with Limited memory, SIAM J. Sci. Comput. 21(1), pp. 24-45, 1999</p>
<dl class="tparams"><dt>Template Parameters</dt><dd>
  <table class="tparams">
    <tr><td class="paramname">Scalar</td><td>the scalar type of the input matrices </td></tr>
    <tr><td class="paramname">UpLo_</td><td>The triangular part that will be used for the computations. It can be Lower or Upper. Default is Lower. </td></tr>
    <tr><td class="paramname">OrderingType_</td><td>The ordering method to use, either AMDOrdering&lt;&gt; or NaturalOrdering&lt;&gt;. Default is AMDOrdering&lt;int&gt;, unless EIGEN_MPL2_ONLY is defined, in which case the default is NaturalOrdering&lt;int&gt;.</td></tr>
  </table>
  </dd>
</dl>
<p>This class follows the <a class="el" href="group__TopicSparseSystems.html#TutorialSparseSolverConcept">sparse solver concept </a>.</p>
<p>It performs the following incomplete factorization: \( S P A P&#39; S \approx L L&#39; \) where L is a lower triangular factor, S is a diagonal scaling matrix, and P is a fill-in reducing permutation as computed by the ordering method.</p>
<p><b>Shifting</b> <b>strategy:</b> Let \( B = S P A P&#39; S \) be the scaled matrix on which the factorization is carried out, and \( \beta \) be the minimum value of the diagonal. If \( \beta &gt; 0 \) then, the factorization is directly performed on the matrix B. Otherwise, the factorization is performed on the shifted matrix \( B + (\sigma+|\beta| I \) where \( \sigma \) is the initial shift value as returned and set by <a class="el" href="classEigen_1_1IncompleteCholesky.html#afe6b11310e22c1853577746a37fbcdc7" title="Set the initial shift parameter .">setInitialShift()</a> method. The default value is \( \sigma = 10^{-3} \). If the factorization fails, then the shift in doubled until it succeed or a maximum of ten attempts. If it still fails, as returned by the <a class="el" href="classEigen_1_1IncompleteCholesky.html#a11a53c3787990c0287f7296f72779509" title="Reports whether previous computation was successful.">info()</a> method, then you can either increase the initial shift, or better use another preconditioning technique. </p>
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  <img id="dynsection-0-trigger" src="closed.png" alt="+"/> Inheritance diagram for Eigen::IncompleteCholesky&lt; Scalar, UpLo_, OrderingType_ &gt;:</div>
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<div class="center"><img src="classEigen_1_1IncompleteCholesky__inherit__graph.png" border="0" usemap="#aEigen_1_1IncompleteCholesky_3_01Scalar_00_01UpLo___00_01OrderingType___01_4_inherit__map" alt="Inheritance graph"/></div>
<map name="aEigen_1_1IncompleteCholesky_3_01Scalar_00_01UpLo___00_01OrderingType___01_4_inherit__map" id="aEigen_1_1IncompleteCholesky_3_01Scalar_00_01UpLo___00_01OrderingType___01_4_inherit__map">
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<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:ad822e66656638a9cf84087ed228514e7"><td class="memTemplParams" colspan="2"><a id="ad822e66656638a9cf84087ed228514e7"></a>
template&lt;typename MatrixType &gt; </td></tr>
<tr class="memitem:ad822e66656638a9cf84087ed228514e7"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#ad822e66656638a9cf84087ed228514e7">analyzePattern</a> (const MatrixType &amp;mat)</td></tr>
<tr class="memdesc:ad822e66656638a9cf84087ed228514e7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Computes the fill reducing permutation vector using the sparsity pattern of <em>mat</em>. <br /></td></tr>
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<tr class="memitem:ad036ff94ea84db68f5c2b6350a885073"><td class="memItemLeft" align="right" valign="top">EIGEN_CONSTEXPR <a class="el" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#ad036ff94ea84db68f5c2b6350a885073">cols</a> () const EIGEN_NOEXCEPT</td></tr>
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<tr class="memitem:ac967d9c0f6fca7fc70ead69cc9c6bd83"><td class="memTemplParams" colspan="2">template&lt;typename MatrixType &gt; </td></tr>
<tr class="memitem:ac967d9c0f6fca7fc70ead69cc9c6bd83"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#ac967d9c0f6fca7fc70ead69cc9c6bd83">compute</a> (const MatrixType &amp;mat)</td></tr>
<tr class="separator:ac967d9c0f6fca7fc70ead69cc9c6bd83"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a715fd8371885458f6317a7d63353b8d5"><td class="memTemplParams" colspan="2">template&lt;typename MatrixType &gt; </td></tr>
<tr class="memitem:a715fd8371885458f6317a7d63353b8d5"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#a715fd8371885458f6317a7d63353b8d5">factorize</a> (const MatrixType &amp;mat)</td></tr>
<tr class="memdesc:a715fd8371885458f6317a7d63353b8d5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Performs the numerical factorization of the input matrix <em>mat</em>.  <a href="classEigen_1_1IncompleteCholesky.html#a715fd8371885458f6317a7d63353b8d5">More...</a><br /></td></tr>
<tr class="separator:a715fd8371885458f6317a7d63353b8d5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a85eaef081ac008cfb2d9fe2c761906f1"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#a85eaef081ac008cfb2d9fe2c761906f1">IncompleteCholesky</a> ()</td></tr>
<tr class="separator:a85eaef081ac008cfb2d9fe2c761906f1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a164f124d27dcc86066eee7abc25f234f"><td class="memTemplParams" colspan="2">template&lt;typename MatrixType &gt; </td></tr>
<tr class="memitem:a164f124d27dcc86066eee7abc25f234f"><td class="memTemplItemLeft" align="right" valign="top">&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#a164f124d27dcc86066eee7abc25f234f">IncompleteCholesky</a> (const MatrixType &amp;matrix)</td></tr>
<tr class="separator:a164f124d27dcc86066eee7abc25f234f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a11a53c3787990c0287f7296f72779509"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__enums.html#ga85fad7b87587764e5cf6b513a9e0ee5e">ComputationInfo</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#a11a53c3787990c0287f7296f72779509">info</a> () const</td></tr>
<tr class="memdesc:a11a53c3787990c0287f7296f72779509"><td class="mdescLeft">&#160;</td><td class="mdescRight">Reports whether previous computation was successful.  <a href="classEigen_1_1IncompleteCholesky.html#a11a53c3787990c0287f7296f72779509">More...</a><br /></td></tr>
<tr class="separator:a11a53c3787990c0287f7296f72779509"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad7b709e4f100630cfd6d8ed90f75aa40"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classEigen_1_1SparseMatrix.html">FactorType</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#ad7b709e4f100630cfd6d8ed90f75aa40">matrixL</a> () const</td></tr>
<tr class="separator:ad7b709e4f100630cfd6d8ed90f75aa40"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8681a4ea582d778eb712a10bb809b1ed"><td class="memItemLeft" align="right" valign="top">const PermutationType &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#a8681a4ea582d778eb712a10bb809b1ed">permutationP</a> () const</td></tr>
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<tr class="memitem:a52df89ac8dba637444a2246574b70593"><td class="memItemLeft" align="right" valign="top">EIGEN_CONSTEXPR <a class="el" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#a52df89ac8dba637444a2246574b70593">rows</a> () const EIGEN_NOEXCEPT</td></tr>
<tr class="separator:a52df89ac8dba637444a2246574b70593"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a79251fafbc557fa3bef58024b7e9c939"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classEigen_1_1Matrix.html">VectorRx</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#a79251fafbc557fa3bef58024b7e9c939">scalingS</a> () const</td></tr>
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<tr class="memitem:afe6b11310e22c1853577746a37fbcdc7"><td class="memItemLeft" align="right" valign="top"><a id="afe6b11310e22c1853577746a37fbcdc7"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1IncompleteCholesky.html#afe6b11310e22c1853577746a37fbcdc7">setInitialShift</a> (RealScalar shift)</td></tr>
<tr class="memdesc:afe6b11310e22c1853577746a37fbcdc7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the initial shift parameter \( \sigma \). <br /></td></tr>
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<tr class="inherit_header pub_methods_classEigen_1_1SparseSolverBase"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classEigen_1_1SparseSolverBase')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classEigen_1_1SparseSolverBase.html">Eigen::SparseSolverBase&lt; IncompleteCholesky&lt; Scalar, Lower, AMDOrdering&lt; int &gt; &gt; &gt;</a></td></tr>
<tr class="memitem:a4a66e9498b06e3ec4ec36f06b26d4e8f inherit pub_methods_classEigen_1_1SparseSolverBase"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classEigen_1_1Solve.html">Solve</a>&lt; <a class="el" href="classEigen_1_1IncompleteCholesky.html">IncompleteCholesky</a>&lt; Scalar, Lower, <a class="el" href="classEigen_1_1AMDOrdering.html">AMDOrdering</a>&lt; int &gt; &gt;, Rhs &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1SparseSolverBase.html#a4a66e9498b06e3ec4ec36f06b26d4e8f">solve</a> (const <a class="el" href="classEigen_1_1MatrixBase.html">MatrixBase</a>&lt; Rhs &gt; &amp;b) const</td></tr>
<tr class="separator:a4a66e9498b06e3ec4ec36f06b26d4e8f inherit pub_methods_classEigen_1_1SparseSolverBase"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3a8d97173b6e2630f484589b3471cfc7 inherit pub_methods_classEigen_1_1SparseSolverBase"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classEigen_1_1Solve.html">Solve</a>&lt; <a class="el" href="classEigen_1_1IncompleteCholesky.html">IncompleteCholesky</a>&lt; Scalar, Lower, <a class="el" href="classEigen_1_1AMDOrdering.html">AMDOrdering</a>&lt; int &gt; &gt;, Rhs &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1SparseSolverBase.html#a3a8d97173b6e2630f484589b3471cfc7">solve</a> (const <a class="el" href="classEigen_1_1SparseMatrixBase.html">SparseMatrixBase</a>&lt; Rhs &gt; &amp;b) const</td></tr>
<tr class="separator:a3a8d97173b6e2630f484589b3471cfc7 inherit pub_methods_classEigen_1_1SparseSolverBase"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aacd99fa17db475e74d3834767f392f33 inherit pub_methods_classEigen_1_1SparseSolverBase"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEigen_1_1SparseSolverBase.html#aacd99fa17db475e74d3834767f392f33">SparseSolverBase</a> ()</td></tr>
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<h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="a85eaef081ac008cfb2d9fe2c761906f1"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a85eaef081ac008cfb2d9fe2c761906f1">&#9670;&nbsp;</a></span>IncompleteCholesky() <span class="overload">[1/2]</span></h2>

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template&lt;typename Scalar , int UpLo_ = Lower, typename OrderingType_  = AMDOrdering&lt;int&gt;&gt; </div>
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          <td class="memname"><a class="el" href="classEigen_1_1IncompleteCholesky.html">Eigen::IncompleteCholesky</a>&lt; Scalar, UpLo_, OrderingType_ &gt;::<a class="el" href="classEigen_1_1IncompleteCholesky.html">IncompleteCholesky</a> </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
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<p>Default constructor leaving the object in a partly non-initialized stage.</p>
<p>You must call <a class="el" href="classEigen_1_1IncompleteCholesky.html#ac967d9c0f6fca7fc70ead69cc9c6bd83">compute()</a> or the pair <a class="el" href="classEigen_1_1IncompleteCholesky.html#ad822e66656638a9cf84087ed228514e7" title="Computes the fill reducing permutation vector using the sparsity pattern of mat.">analyzePattern()</a>/factorize() to make it valid.</p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="classEigen_1_1IncompleteCholesky.html#a164f124d27dcc86066eee7abc25f234f">IncompleteCholesky(const MatrixType&amp;)</a> </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a164f124d27dcc86066eee7abc25f234f">&#9670;&nbsp;</a></span>IncompleteCholesky() <span class="overload">[2/2]</span></h2>

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template&lt;typename Scalar , int UpLo_ = Lower, typename OrderingType_  = AMDOrdering&lt;int&gt;&gt; </div>
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template&lt;typename MatrixType &gt; </div>
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          <td class="memname"><a class="el" href="classEigen_1_1IncompleteCholesky.html">Eigen::IncompleteCholesky</a>&lt; Scalar, UpLo_, OrderingType_ &gt;::<a class="el" href="classEigen_1_1IncompleteCholesky.html">IncompleteCholesky</a> </td>
          <td>(</td>
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<p>Constructor computing the incomplete factorization for the given matrix <em>matrix</em>. </p>

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<h2 class="groupheader">Member Function Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#ad036ff94ea84db68f5c2b6350a885073">&#9670;&nbsp;</a></span>cols()</h2>

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template&lt;typename Scalar , int UpLo_ = Lower, typename OrderingType_  = AMDOrdering&lt;int&gt;&gt; </div>
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          <td class="memname">EIGEN_CONSTEXPR <a class="el" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> <a class="el" href="classEigen_1_1IncompleteCholesky.html">Eigen::IncompleteCholesky</a>&lt; Scalar, UpLo_, OrderingType_ &gt;::cols </td>
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<dl class="section return"><dt>Returns</dt><dd>number of columns of the factored matrix </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#ac967d9c0f6fca7fc70ead69cc9c6bd83">&#9670;&nbsp;</a></span>compute()</h2>

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template&lt;typename Scalar , int UpLo_ = Lower, typename OrderingType_  = AMDOrdering&lt;int&gt;&gt; </div>
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template&lt;typename MatrixType &gt; </div>
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          <td class="memname">void <a class="el" href="classEigen_1_1IncompleteCholesky.html">Eigen::IncompleteCholesky</a>&lt; Scalar, UpLo_, OrderingType_ &gt;::compute </td>
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<p>Computes or re-computes the incomplete Cholesky factorization of the input matrix <em>mat</em> </p>
<p>It is a shortcut for a sequential call to the <a class="el" href="classEigen_1_1IncompleteCholesky.html#ad822e66656638a9cf84087ed228514e7" title="Computes the fill reducing permutation vector using the sparsity pattern of mat.">analyzePattern()</a> and <a class="el" href="classEigen_1_1IncompleteCholesky.html#a715fd8371885458f6317a7d63353b8d5" title="Performs the numerical factorization of the input matrix mat.">factorize()</a> methods.</p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="classEigen_1_1IncompleteCholesky.html#ad822e66656638a9cf84087ed228514e7" title="Computes the fill reducing permutation vector using the sparsity pattern of mat.">analyzePattern()</a>, <a class="el" href="classEigen_1_1IncompleteCholesky.html#a715fd8371885458f6317a7d63353b8d5" title="Performs the numerical factorization of the input matrix mat.">factorize()</a> </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a715fd8371885458f6317a7d63353b8d5">&#9670;&nbsp;</a></span>factorize()</h2>

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template&lt;typename Scalar , int UpLo_ = Lower, typename OrderingType_  = AMDOrdering&lt;int&gt;&gt; </div>
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template&lt;typename MatrixType &gt; </div>
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<p>Performs the numerical factorization of the input matrix <em>mat</em>. </p>
<p>The method <a class="el" href="classEigen_1_1IncompleteCholesky.html#ad822e66656638a9cf84087ed228514e7" title="Computes the fill reducing permutation vector using the sparsity pattern of mat.">analyzePattern()</a> or <a class="el" href="classEigen_1_1IncompleteCholesky.html#ac967d9c0f6fca7fc70ead69cc9c6bd83">compute()</a> must have been called beforehand with a matrix having the same pattern.</p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="classEigen_1_1IncompleteCholesky.html#ac967d9c0f6fca7fc70ead69cc9c6bd83">compute()</a>, <a class="el" href="classEigen_1_1IncompleteCholesky.html#ad822e66656638a9cf84087ed228514e7" title="Computes the fill reducing permutation vector using the sparsity pattern of mat.">analyzePattern()</a> </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a11a53c3787990c0287f7296f72779509">&#9670;&nbsp;</a></span>info()</h2>

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template&lt;typename Scalar , int UpLo_ = Lower, typename OrderingType_  = AMDOrdering&lt;int&gt;&gt; </div>
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          <td class="memname"><a class="el" href="group__enums.html#ga85fad7b87587764e5cf6b513a9e0ee5e">ComputationInfo</a> <a class="el" href="classEigen_1_1IncompleteCholesky.html">Eigen::IncompleteCholesky</a>&lt; Scalar, UpLo_, OrderingType_ &gt;::info </td>
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<p>Reports whether previous computation was successful. </p>
<p>It triggers an assertion if <code>*this</code> has not been initialized through the respective constructor, or a call to <a class="el" href="classEigen_1_1IncompleteCholesky.html#ac967d9c0f6fca7fc70ead69cc9c6bd83">compute()</a> or <a class="el" href="classEigen_1_1IncompleteCholesky.html#ad822e66656638a9cf84087ed228514e7" title="Computes the fill reducing permutation vector using the sparsity pattern of mat.">analyzePattern()</a>.</p>
<dl class="section return"><dt>Returns</dt><dd><code>Success</code> if computation was successful, <code>NumericalIssue</code> if the matrix appears to be negative. </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#ad7b709e4f100630cfd6d8ed90f75aa40">&#9670;&nbsp;</a></span>matrixL()</h2>

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template&lt;typename Scalar , int UpLo_ = Lower, typename OrderingType_  = AMDOrdering&lt;int&gt;&gt; </div>
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          <td class="memname">const <a class="el" href="classEigen_1_1SparseMatrix.html">FactorType</a>&amp; <a class="el" href="classEigen_1_1IncompleteCholesky.html">Eigen::IncompleteCholesky</a>&lt; Scalar, UpLo_, OrderingType_ &gt;::matrixL </td>
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<dl class="section return"><dt>Returns</dt><dd>the sparse lower triangular factor L </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a8681a4ea582d778eb712a10bb809b1ed">&#9670;&nbsp;</a></span>permutationP()</h2>

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<dl class="section return"><dt>Returns</dt><dd>the fill-in reducing permutation P (can be empty for a natural ordering) </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a52df89ac8dba637444a2246574b70593">&#9670;&nbsp;</a></span>rows()</h2>

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template&lt;typename Scalar , int UpLo_ = Lower, typename OrderingType_  = AMDOrdering&lt;int&gt;&gt; </div>
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          <td class="memname">EIGEN_CONSTEXPR <a class="el" href="namespaceEigen.html#a62e77e0933482dafde8fe197d9a2cfde">Index</a> <a class="el" href="classEigen_1_1IncompleteCholesky.html">Eigen::IncompleteCholesky</a>&lt; Scalar, UpLo_, OrderingType_ &gt;::rows </td>
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<dl class="section return"><dt>Returns</dt><dd>number of rows of the factored matrix </dd></dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a79251fafbc557fa3bef58024b7e9c939">&#9670;&nbsp;</a></span>scalingS()</h2>

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template&lt;typename Scalar , int UpLo_ = Lower, typename OrderingType_  = AMDOrdering&lt;int&gt;&gt; </div>
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          <td class="memname">const <a class="el" href="classEigen_1_1Matrix.html">VectorRx</a>&amp; <a class="el" href="classEigen_1_1IncompleteCholesky.html">Eigen::IncompleteCholesky</a>&lt; Scalar, UpLo_, OrderingType_ &gt;::scalingS </td>
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<dl class="section return"><dt>Returns</dt><dd>a vector representing the scaling factor S </dd></dl>

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<hr/>The documentation for this class was generated from the following file:<ul>
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